technical_indicators

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that indicators are computed locally and incur no API cost, which is useful behavioral context. It also implies a read-only, synchronous calculation. However, it does not mention potential latency, data source dependencies, or whether the buy/sell signals are derived or user-interpreted—minor gaps given the tool's nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: a one-sentence purpose, a list of indicators, market scope, and a formatted Args section followed by practical examples. Every sentence adds value, and the markdown formatting improves scannability without unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 3 parameters with 0% schema coverage and an output schema exists, the description provides all necessary context for invocation: parameter meanings, default values, allowed values, and examples. It covers both basic and advanced usage scenarios, making it complete for an agent to select and call the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates. It explains every parameter with allowable values (period: 3mo, 6mo, 1y, 2y; indicators: comma-separated list with exact option names; symbol: examples like RELIANCE, AAPL) and clarifies the default behavior ('Leave empty for ALL indicators'). Examples show positional argument order, which adds significant meaning beyond the schema's bare string types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a specific verb phrase 'Compute technical indicators for a stock with buy/sell signals' and enumerates the exact indicators (RSI, MACD, SMA, EMA, Bollinger Bands, ATR, Stochastic, ADX, OBV). This clearly distinguishes the tool from siblings that focus on quotes, historical data, or fundamental analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on supported markets ('Indian (NSE/BSE) and US stocks') and gives concrete usage examples with different parameter combinations. It does not explicitly state when to prefer this over alternatives or exclude scenarios, but the examples and indicator list make the intended use obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.